From the Newsroom
Red Hat Delivers Accessible, Open Source Generative AI Innovation with Red Hat Enterprise Linux AI
- The offering is the first to deliver supported, indemnified and open source-licensed IBM Granite LLMs under Red Hat’s flexible and proven enterprise subscription model
- Adds open source InstructLab model alignment tools to the world’s leading enterprise Linux platform to simplify generative AI model experimentation and alignment tuning
- Provides a supported, enterprise-ready model runtime environment across AMD, Intel and NVIDIA platforms for fueling AI innovation built on open source
IBM Expands Software Availability to 92 Countries in AWS Marketplace
IBM's software portfolio availability is expanding globally to 92 countries in AWS Marketplace, a digital catalog with thousands of software listings from independent software vendors (ISVs) that make it easy to find, test, buy, and deploy software that runs on Amazon Web Services (AWS). The expansion beyond Denmark, France, Germany, United Kingdom and United States, where the software is currently available, will help make procurement easier for clients, streamline purchasing and create new efficiencies, while allowing them to use their AWS committed spend for IBM software purchases.
LTIMindtree and IBM Collaborate on watsonx Center of Excellence for Generative AI
The LTIMindtree and IBM CoE plans to offer a comprehensive suite of services, combining LTIMindtree's expertise in data and machine learning model customization and full-stack engineering with IBM watsonx technology including watsonx.ai, watsonx.data, and watsonx.governance, and AI assistants. The center, located in India, will focus on building point solutions to accelerate clients’ generative AI adoption journeys.
Community Stories
The EU AI Act - Driving New Levels of Human Oversight and Regulatory Compliance for AI
The primary focus of the EU AI Act is to strengthen regulatory compliance in the areas of risk management, data protection, quality management systems, transparency, human oversight, accuracy, robustness and cyber security. It aims to drive transparency and accountability into how AI systems are developed and deployed, helping to ensure that AI products placed in the market are safe for individuals to use.
AI Governance with watsonx
It is important to highlight that AI governance applies not only to generative AI, as all AI models need governance and attention, including machine learning models to identify trends and patterns in data. Governing and monitoring these models to ensure they are explainable and transparent are crucial. As a real example, imagine a bank that has a predictive AI model to analyze loan applications and may need detailed explanations of its decisions in case of an audit process.
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